
I conduct research in artificial intelligence and hyperspectral imaging, focusing on advanced computational methods for analysing tropical forests, tree-ring structures and climate-related variation. My work spans the full hyperspectral workflow, including acquisition, calibration, modelling and interpretation, with emphasis on deep learning approaches tailored to remote sensing challenges. During my PhD, I developed efficient AI models designed to operate with limited labelled data and reduced computational requirements. I also apply hyperspectral analysis across multiple domains, including remote sensing, forensic imaging and medical diagnostics. In parallel, I have industry experience building and deploying applied AI solutions, and I maintain a strong interest in developing reliable, well-structured and efficient programming solutions for complex data-driven problems.
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